<div class=content>
	<h2>Python API</h2>
	<p>
		<a target="_blank" href="https://docs.python.org/3/index.html">Python 文档</a>: 
		<a target="_blank" href="https://docs.python.org/3/tutorial/index.html">tutorial</a>, 
		<a target="_blank" href="https://docs.python.org/3/reference/index.htmll" class="button pink">Language Reference</a>, 
	</p>
	<p>
		<a target="_blank" href="https://docs.python.org/3/py-modindex.html">Python 标准库</a>:  
		<a target="_blank" href="https://docs.python.org/3/library/index.html#library-index" class="button pink">Standard Library</a>, 
	</p>
	
	<h2>Python重要的包</h2>
	<pre class=saying>唯有坚持远离自己的舒适区，努力拓展自己的知识边界，才能真正到达专家的水平。</pre>	
	<p>Python 数据分析的底层基石 Numpy； Python 数据清洗大杀器 Pandas。</p>
	<img class="banner" src='data/Python/images/SciPy_ecosystem.png'>
	
	<p><a target="_blank" href="http://www.numpy.org/">NumPy</a>是Python科学计算的基础包，很多库是基于NumPy构建的。高效的 数组和矩阵运算作为底层支持。<a target="_blank" href="https://docs.scipy.org/doc/numpy/user/quickstart.html">&gt;&gt;np Quickstart tutorial</a></p>
	
	<p><a target="_blank" href="https://docs.scipy.org/doc/scipy/reference/">SciPy</a> 是一组专门解决科学计算中各种标准问题域的包的集合。SciPy与NumPy有机结合完全可以替代MATLAB的计算功能。</p>
	<p><a target="_blank" href="http://pandas.pydata.org/">pandas</a> 快速便捷处理结构化数据的大量数据结构和函数。其中DataFrame和R的data.frame类似，但是功能更多。</p>
	<p><a target="_blank" href="https://matplotlib.org/gallery/index.html" title="Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.">Matplotlib</a> 是最流行的Python库，非常适合创建出版物上用的图表。和IPython结合的很好，提供交互式数据绘图环境，绘制的图表也是交互式的。</p>
	<hr />
	
	<p><a target="_blank" href="http://seaborn.pydata.org/index.html">Seaborn</a>是一个在Python中制作有吸引力和丰富信息的统计图形的库。它构建在 matplotlib 之上，应该把Seaborn视为matplotlib的补充，而不是替代物。同时它能高度兼容numpy与pandas数据结构以及scipy与statsmodels等统计模式。掌握seaborn能很大程度帮助我们更高效的观察数据与图表，并且更加深入了解它们。 Seaborn 其实是在matplotlib的基础上进行了更高级的 API 封装，从而使得作图更加容易。
	在大多数情况下使用seaborn就能做出很具有吸引力的图，而使用matplotlib就能制作具有更多特色的图。| <a target="_blank" href="http://seaborn.pydata.org/api.html">API 文档</a>, <a target="_blank" href="http://seaborn.pydata.org/tutorial.html">tutorial 教程</a></p>
	
	
	
	<p><a target="_blank" href="https://ipython.org/" title="IPython provides a rich architecture for interactive computing with: A powerful interactive shell; A kernel for Jupyter; ...">IPython</a> 是一个增强的Python shell。主要用于交互式数据处理和利用matplotlib数据进行可视化处理。Project <a target="_blank" href="https://jupyter.org/">Jupyter</a> exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.</p>
	
	<p> 相关博客：
		<a target="_blank" href="https://www.gairuo.com/">Pandas 博客</a>
	</p>
	
	
	
	<pre class=saying>把简单和选择留给别人，把复杂和无奈留给自己。-- 做工具的人</pre>
	
	<h3>机器学习 ML</h3>
	<p><a target="_blank" href="https://scikit-learn.org/stable/">scikit-learn</a> 通用机器学习库: Machine Learning in Python. 1.Simple and efficient tools for data mining and data analysis; 2.Accessible to everybody, and reusable in various contexts; 3.Built on NumPy, SciPy, and matplotlib; 4.Open source, commercially usable - BSD license; </p>






	<h3>深度学习 DL</h3>
	<p><a target="_blank" href="https://www.cbedai.net/thinker/">人工智能授课笔记</a> </p>
	
	<p><a target="_blank" href="https://keras.io/">Keras</a> The Python Deep Learning library; 集成深度学习中各类成熟的算法，易于AI初学者安装和使用。keras是构建在tensorflow基础上的python第三方库，专门用于神经网络的构建与计算，同时还集成了scikit-learn库，使得可以在神经网络的构建中运用机器学习的方法。| <a target="_blank" href="https://keras.io/api/applications/">Keras model zoos</a></p>
		
	<p><a target="_blank" href="https://pytorch.org/">PyTorch</a> (<a target="_blank" href="https://www.zhihu.com/question/65578911/answer/565574377">知乎: PyTorch 好在哪里?</a> | 
	<a target="_blank" href="https://pytorch.org/hub/">PyTorch hub</a>
	)2017年1月，由Facebook人工智能研究院（FAIR）基于Torch推出了PyTorch。FROM RESEARCH TO PRODUCTION.
An open source machine learning framework that accelerates the path from research prototyping to production deployment. </p>
	
	
	<p><a target="_blank" href="https://www.tensorflow.org/">Tensorflow</a>是一个端到端开源机器学习平台。[大概是废了，有很多劝退的] </p>
	<p><b>实战平台</b>:  
		<a target="_blank" href="https://www.kaggle.com/">Kaggle算法大赛平台</a> 
		和 
		<a target="_blank" href="https://www.openml.org/">OpenML平台</a>
	</p>







	
	
	
	<hr>
	<p><b class=red>教科书</b>: <a target="_blank" href="https://www.deeplearningbook.org/">Deep Learnin (Ian Goodfellow, MIT press, 2016)</a> 全书完整在线。<a target="_blank" href="https://github.com/exacity/deeplearningbook-chinese">Deep Learning 中文版在 Github 开源</a>，可以在 release 中下载pdf版。 </p>

	<p><b>教程:</b>
		<a target="_blank" href="https://github.com/trekhleb/homemade-machine-learning" title="线性回归、logistic回归、k-means聚类、神经网络">机器学习原理与代码</a>
		<a target="_blank" href="https://zh.d2l.ai/" title="" class="button pink">动手学深度学习(D2L)-李沐</a>
	</p>

	<p>很多实体书，虽然不算年代非常的久远，但是Python语言的发展日新月异，很多函数、语法之类的都已经和之前大不相同，<b>只有一直保持着学习的心思才有可能不被时代所落下。</b></p>

	<p>知乎 <a target="_blank" href="https://www.zhihu.com/question/24590883/answer/92420471">哪些 Python 库让你相见恨晚？</a>, refer <a target="_blank" href="https://github.com/jobbole/awesome-python-cn">Python 资源大全(github)</a></p>
	
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<a target="_blank" href="xx">xx</a>
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	<h2>项目描述</h2>
	<p><a target='_blank' href='https://www.python.org/' title='python'>Python官网</a>, Python is a programming language that lets you work quickly and integrate systems more effectively.</p>
	
	<p>推荐使用 Jupyter Notebook 学习和编写Python，体验很好。The <a target='_blank' href='https://jupyter.org' title='jupyter notebook'>jupyter notebook</a> is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
	
	<br>
The Notebook has support for over 40 programming languages, including Python, R, Julia, and Scala.</p>


	
	


	
	<p><a target='_blank' href='https://pypi.python.org/pypi' title='python'>PyPI - the Python Package Index</a>:The Python Package Index is a repository of software for the Python programming language. There are currently 90241 packages here.(2016-10-7)</p>
	<p><a target='_blank' href='http://biopython.org/wiki/Biopython' title='python'>biopython</a>:Biopython is a set of freely available tools for biological computation written in Python by an international team of developers.<a href='http://biopython.org/DIST/docs/tutorial/Tutorial.html' target='_blank'>Biopython Tutorial and Cookbook</a></p>






	<p>With over 6 million users, the open source <a target='_blank' href='https://www.anaconda.com' title='anaconda'>Anaconda</a> Distribution is the fastest and easiest way to do Python and R data science and machine learning on Linux, Windows, and Mac OS X. It's the industry standard for developing, testing, and training on a single machine.  Anaconda具有跨平台、包管理、环境管理的特点，因此很适合快速在新的机器上部署Python环境。
	<a target='_blank' href='https://conda.io/docs/_downloads/conda-cheatsheet.pdf'>Conda cheat sheet.pdf</a> | 
	<a target='_blank' href='https://docs.anaconda.com/anaconda/user-guide/getting-started'>docs</a>
	</p>



	<p> One document to learn numerics, science, and data with Python <a target='_blank' href='https://www.scipy-lectures.org/index.html' title='Python Course'>Scipy Lecture Notes</a>:  
	Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. 
	</p>



<h2>学习指南</h2>
	<p>python3:<a target='_blank' href='https://www.python.org/downloads/' title='下载'>下载</a> | 
	<a target='_blank' href='https://docs.python.org/3/' title='文档'>文档</a> | 
	<a target='_blank' href='http://study.163.com/course/introduction/1000035.htm#/courseDetail' title='收费'>网易公开课-python目录-收费</a> | 
	<a target='_blank' href='http://rosalind.info/problems/locations/' title='免费'>rosalind Python问题</a> | 
	
	廖雪峰老师的<a target='_blank' href='http://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000'>Python 3教程</a> | 
   runoob上的<a target='_blank' href='http://www.runoob.com/python3/python3-tutorial.html' title=''>Python 3 教程</a> | 
   <a target='_blank' href='https://tendcode.com/about/' title=''>用Django 写的博客</a> | 
   <a target='_blank' href='https://python.swaroopch.com/' title='在线Python入门书english'>《A Byte of Python》</a> | 
   <a target='_blank' href='https://runestone.academy/runestone/books/published/pythonds/index.html' title='Problem Solving with Algorithms and Data Structures using Python' class="button blue">Python版的算法和数据结构课</a> | 
   <a target='_blank' href='https://www.voidking.com/categories/专业/后端/python/' title=''>Python(web/图像)</a> | 
   <a target='_blank' href='http://liyangbit.com/tutorials/' title=''>Python教程(numpy/pandas)</a> | 
   <a target='_blank' href='https://www.imooc.com/learn/1110' title=''>Django入门视频</a> | 
   
	</p>


	<p><b>进阶内容: </b>Python高阶函数、装饰器，反射、元编程、各种魔术方法，Python的解释器运行机制是什么？垃圾回收原理是什么？为什么Python多线程鸡肋？GIL无解了吗？做个Python版的ls和find，功能要逐步完备，尽可能媲美Linux的同名命令。</p>

<pre>
正则数量词
	? {0,1}
	* {0,}
	+ {1,}
开发工具: sublime, vim, pycharm, ipython[notebook]
web框架: flask, django, web.py, web2py, FastAPI, 
数据库: mysql, redis, mongo
数据处理: pandas, numpy, scipy, sklearn
业务框架: spark, hadoop, AWS, docker
</pre>








	<h2>Project list</h2>
	<p>项目1：<a target='_blank' href="https://github.com/BioMooc/txtBlog.py" class="external text">txtBlog.py</a>一个基于python3 flask包的文本博客系统。作用是：记录和管理知识。<a target='_blank' href="https://github.com/miostudio/txtBlog.py">我的实例@笔记本电脑</a>。</p>
	
	<p>项目2：<a target='_blank' href="https://github.com/BioMooc/webPan.py" class="external text">webPan.py</a>一个基于python3 flask包的简易网盘系统。作用是：局域网内传小文件不需要用U盘了。<a target='_blank' href="http://y.biomooc.com:8000/list">本地实例 @Y</a>。</p>
	
	<p>项目3：<a target='_blank' href="https://gitee.com/dawnEve/dawnTodo.py" class="external text">dawnTodo.py</a>: Flask + Vue3 + Sqlite3 的日程/任务管理系统。<a target='_blank' href="http://j3.biomooc.com:8500/#/">本地实例 @J3</a>。</p>







	<h2>学习目标</h2>
<pre>
1.
廖雪峰网站看一遍，习题做一遍。
学会调试。
学会google。

python挑战赛 
http://www.pythontip.com/coding/code_oj_case/1



2.
然后我们公司在面试的时候一般会要求面试者做两道题：
1、写一个爬虫（用线程池等）
2、写个论坛程序
别乍一看觉得挺简单的，怎么写好一个爬虫是有很多讲究的；

然后写论坛程序，可以学习Python的Web框架，如web.py Django等
另外，只有一点，边学边码，实践才是大道理，在计算机的世界，说的再多，不去做，都是扯淡。。。

作者：Fooying
链接：https://www.zhihu.com/question/23234538/answer/24004374


3.
30天尝试新事情 http://30daydo.com
python爬虫 推送知乎文章到kindle电子书
python 暴力破解wordpress博客后台登陆密码
批量获取色影无忌图片 Python_小组
用python破解某211大学BBS论坛用户密码


4.python作业代写



5.进一步学习模块
掌握Python基本数据分析方法、强大高效的数据分析环境 – Pandas、
Python数据可视化工具 -- Pyplot、
科学计算的基础 – NumPy、
通过不同案例讲解与模拟操作掌握Python语言实施数据科学项目的方法，
通过手把手的实操指导，掌握Python语言数据处理方法与编程技术
</pre>
	
</div>
	